Sensors 2015, 15, 2006-2020; doi:10.3390/s150102006

sensors ISSN 1424-8220

www.mdpi.com/journal/sensors

Article

Design and Testing of an Agricultural Implement for Underground Application of Rodenticide Bait

Hugo Malón, A. Javier Aguirre, Antonio Boné, Mariano Vidal and F. Javier García-Ramos *

Superior Polytechnic School, University of Zaragoza, Huesca 22071, Spain;

E-Mails: hml@unizar.es (H.M.); javier.aguirre@unizar.es (A.J.A.); anbone@unizar.es (A.B.);

vidalcor@unizar.es (M.V.)

* Author to whom correspondence should be addressed; E-Mail: fjavier@unizar.es;

Tel.: +34-914-239-301; Fax: +34-974-239-302.

Academic Editor: Gonzalo Pajares Martinsanz

Received: 9 November 2014 / Accepted: 7 January 2015 / Published: 16 January 2015

Abstract: An agricultural implement for underground application of rodenticide bait to

control the Mediterranean pocket gopher (Microtus Duodecimcostatus) in fruit orchards

has been designed and tested. The main objective of this research was to design and test the

implement by using the finite element method (FEM) and considering a range of loads

generated on most commonly used furrow openers in agricultural implements. As a second

step, the prototype was tested in the field by analysing the effects of forward speed and

application depth on the mechanical behaviour of the implement structure. The FEM was

used in the design phase and a prototype was manufactured. The structural strains on the

prototype chassis under working conditions were tested by using strain gauges to validate the

design phase. Three forward speeds (4.5, 5.5, and 7.0 km/h), three application depths (0.12,

0.15, and 0.17 m), and two types of soil (clayey-silty-loam and clayey-silty-sandy) were

considered. The prototype was validated successfully by analysing the information obtained

from the strain gauges. The Von Mises stresses indicated a safety coefficient of 1.9 for the

most critical load case. Although both forward speed and application depth had a significant

effect on the stresses generated on the chassis, the latter parameter critically affected the

structural behaviour of the implement. The effects of the application depth on the strains

were linear such that strains increased with depth. In contrast, strains remained roughly

constant regardless of variation in the forward speed.

OPEN ACCESS

Sensors 2015, 15 2007

Keywords: FEM; strain gauge; pocket gopher; plough

1. Introduction

Different types of moles and pocket gophers can cause damage to agricultural crops [1]. One such

species is the Mediterranean pocket gopher (Microtus Duodecimcostatus), whose natural habitat

includes the southeast of France and the northeast, central, and southern zones of the Iberian Peninsula.

These pocket gophers are small underground rodents that weigh between 19 and 32 g; they are 9 to 11 cm

long (head and body) with a tail of about 3 cm. These animals excavate corridors, which they use as

shelter and breeding areas. The species is exclusively vegetarian and causes irreversible damage to

agricultural crops.

Damage to agricultural crops has been reported by different authors. Apple trees are particularly

susceptible to feeding damage during winter periods when voles feed on bark, vascular tissues and

roots [2]. Populations of 1700 voles per acre (4250 voles/ha) in Washington State apple orchards

decreased production by 35% [3]. In Europe, the common vole is a major vertebrate pest for plant

production that can cause important economic losses during outbreaks [4]. In a survey carried out

between 75 apple orchards in Germany [5], on 17% of the farms no damage occurred although vole

species were present, 55% of the farmers reported a loss of up to 10% of apple trees/ha, 19% of the

farmers lost up to a fourth and two farmers suffered from a total loss of trees. Damage occurred

although the vole populations were controlled permanently.

Several techniques are currently used to combat pocket gophers: agricultural implements (burrow

builders) pulled by a tractor to apply rodenticide bait underground; manual equipment to locally apply

rodenticide bait underground; seasonal ploughing to destroy pocket gopher corridors; manual

equipment to generate shock waves (by combustion of gas mixtures) in pocket gopher corridors;

fumigation equipment; trapping equipment; and biological control. Burrow builders pulled by a tractor

are used most successfully when there are large fields that have extensive pocket gopher populations at

high densities due to its higher working capacity over other techniques [6].

For this reason, for extensive crops and fruit orchards, the most common techniques to combat

pocket gophers are based on the underground application of rodenticide baits [6,7] by using modified

mole ploughs [8]. In these techniques, the application depth and proper burial of the bait (without

tilling) are the key factors for successful treatment [9]. A second work parameter, forward speed, is

important because it is directly related to the time used to carry out the work. Importantly, valid solutions

for a certain type of pocket gopher (genus Microtus) are not applicable to other types (genus Thomomys,

Talpa, or Arvicola); therefore, specific solutions must be analysed for each type of pocket gopher.

Existing equipment for underground application of rodenticide baits were designed in USA [6] to

fight voles of the genus Thomomys that are large rodents, between 15 and 30 cm. The equipment

creates an underground tunnel of large diameter using a torpedo tube and produces a tilling of the land.

Subsequently, this machine has been used in Europe for the fight against other smaller voles, in this

case genus Avicola and Talpa [10], both larger than the genus Microtus (Mediterranean vole). The

Sensors 2015, 15 2008

application of this machine in combating the Mediterranean vole has not been successful mainly due to

the excessive size of the tunnel generated and the difficulty of producing a closure thereof.

Research carried out to develop agricultural implements has provided information on the force

exerted by the ground over furrow opening systems depending on the type of soil [11], the working

speed and depth [12], and the characteristics of implements such as mouldboard ploughs [13], mole

ploughs [8], shallow ammonia injectors [14], spot ploughs [15], weed harrows [16], and seeders [17].

However, developing an agricultural implement to apply rodenticide bait against the Mediterranean

pocket gopher requires specific research to optimise the performance of the machine. In this context,

numerical analysis by the Finite Element Method (FEM) is a common technique used to design and

develop vehicles as well as machine prototypes [18,19]. The technique is also used to design

agricultural implements [20,21].

The FEM allows one to simulate the behaviour of a machine under working conditions. Once a

machine is developed, experimental data are required to validate the design phase and to understand in

detail the effect of the working conditions on the mechanical behaviour of the implement. To analyse

the mechanical behaviour of a machine in the field, several types of sensors are used, including

variable displacement transducers, potentiometers, and strain gauges. The use of strain gauges is

widespread in the agricultural machinery sector [21,22] because such gauges are the most cost-effective

and reliable solution to measure material stress in the field [23]. The gauges also supply information

about deformations of the implement structure and can be calibrated as force transducers [15]. The

numerical analysis allows one to locate the optimal areas for strain gauge placement and perform

optimal comparative analyses of numerical and experimental results.

The main objective of this research was to design and test an agricultural implement for

underground application of rodenticide bait in fruit orchards. To this end, a machine prototype was

developed as a first step by using FEM and considering a range of loads generated on most commonly

used furrow openers in agricultural implements. As a second step, the prototype was tested in the field

to validate the design by analysing the effects of forward speed and application depth on the

mechanical behaviour of the implement structure.

2. Experimental Section

2.1. Prototype Design

Numerical techniques have been employed to design the prototype. In this phase, a software based

in the FEM has been used, concretely the software Abaqus 6.12 (DS Simulia—Providence, RI, USA).

As a result, an agricultural implement prototype for the underground application of rodenticide bait

was developed and fabricated.

The prototype, designed to apply rodenticide bait in fruit orchards, is composed of two parts: a fixed

chassis and a mobile chassis. The fixed chassis is attached to the tractor linkage system. The mobile

chassis is designed to revolve around one of the ends of the fixed chassis so that the machine is

reduced in width and be driven on public roads. This machine design allows the operator to place the

rodenticide bait dispenser near the tree line. This area is inhabited by the Mediterranean pocket

gophers owing to its proximity to the drip lines.

Sensors 2015, 15 2009

The rodenticide bait is applied in a completely mechanical fashion. The implement consists of a

furrow opener linked to a bait dispenser so that the product is deposited underground in the area near

the tree line. Once the bait is deposited, a metal roller closes the furrow. The metal roller also acts as

the drive element of the dispenser.

The mobile chassis of the agricultural implement consists of the following components (Figure 1):

furrow opener, rodenticide bait dispenser, and metal roller to close the furrow and to activate the

rodenticide bait dispenser. The furrow opener consists of a rigid tine, 2 cm in width. A narrow tine was

selected with the goal of create tunnels in line with the size of the Mediterranean vole. The implement

was designed to work at a depth of 15 cm according to previous experiences carried out in Europe to

fight against small voles by applying underground rodenticide bait [10]. The bait dispenser consists of

a horizontal rotating disk with holes, placed on the bottom of a rodenticide bait reservoir. The disk

receives the turning movement through a mechanical transmission driven by the metal roller. The

rotating disk delivers the bait, located in the holes, to the tunnel generated by the furrow opener.

Figure 1. Components of the agricultural implement prototype: (1) fixed chassis;

(2) mobile chassis; (3) furrow opener; (4) rodenticide bait dispenser; (5) metal roller.

In the first phase of the numerical analysis, a series of documents [17,24–26] were consulted to

establish the furrow opener geometry. The chassis geometry was set according to the experience of the

research group and existing designs of implements with a certain similarity [8,14]. Once the geometry

was completed, a finite element model of the agricultural implement was discretised.

The numerical model, shown in Figure 2, consists of 44,665 nodes and 43,399 elements. The

elements used were of the shell type in all components except the metal roller, which was discretised

by bar elements and mass elements. The main dimensions of the prototype are shown in Table 1.

The boundary conditions imposed in the numerical analysis prevented movement in the three areas

at which the agricultural implement was attached to the tractor. These areas are shown in red in Figure 2.

Five load cases were analysed, which correspond to typical values of forces considering different

types of furrow openers at depths around 0.15 m [27]. Loads were applied at the furrow opener

(in blue in Figure 2). The five load cases considered were 445, 800, 2610, 4500, and 5000 N. The

components of the prototype were designed and manufactured by using ST-52 steel (yield strength,

360 MPa). Information provided by the numerical analysis allowed us to identify the critical and

Sensors 2015, 15 2010

oversized areas of the prototype in the design phase. Furthermore, the numerical results allowed us to

determine the number of strain gauges and optimal areas for their placement to obtain an optimal

comparative analysis of numerical and experimental results.

Table 1. Dimensions of the prototype.

Prototype Dimensions Value (m)

Fixed Chassis Width 1.750 Mobile Chassis Width 1.844

Distance between the bottom of the fixed chassis and the bottom of the mobile chassis 0.19 Distance between the bottom of the mobile chassis and the bottom of the furrow opener 0.38

Working distance (Distance between the centre of the tractor and the furrow opener) 2.110

Figure 2. Finite element model of the prototype for underground application of rodenticide

bait. Areas of load application (furrow opener, in blue) and boundary conditions

(attachment to the tractor, in red).

As an example, Figure 3 shows the Von Mises stresses obtained from the load case in which a force

of 2160 N was applied to the furrow opener.

Figure 3. Results of Von Mises stress from the load case in which a force of 2610 N was

applied to the furrow opener.

Sensors 2015, 15 2011

2.2. Experimental Measurements

The agricultural implement prototype was built once the numerical analysis by the FEM was

completed. To record the strains in the prototype during the tests, a rosette (strain gauge 1) and three

linear strain gauges (gauges 2–4) were installed in the prototype. The type and location of the strain

gauge were determined from the results of the numerical analysis. Strain gauges supplied the

experimental data required to validate the information obtained from the FEM simulation. Besides, the

strain values let one analyze the effect of the forward speed and application depth on the structural

behaviour of the implement.

The choice of sensor type depended on the stresses obtained in the numerical analysis. Specifically,

linear strain gauges were used in areas in which the stress value in one direction was greater than the

values in the other directions. In the case of the rosette, the numerical analysis showed that the in-plane

stresses were similar for all directions.

The four sensors were located in critical areas, in which the stress gradients were low. The locations

of the strain gauges are shown in Figure 4. A fourth unidirectional strain gauge was installed to correct

the effects of noise and temperature recorded by the strain gauges.

Figure 4. Strain gauge locations on the agricultural implement prototype during the experimental tests.

The experimental tests involved a combination of three variables: forward speed, application depth,

and type of soil. Three forward speeds (4.5, 5.5, and 7.0 km/h), three application depths (0.12, 0.15,

and 0.17 m), and two types of soil (clayey-silty-loam and clayey-silty-sandy, Table 2) were

considered. For each combination of variables, continuous measurements were taken considering a

pathway of 400 m. Thus, 18 pathways of 400 m were tested in total, nine for each type of soil.

The strain gauge signals were recorded at a frequency of 5 Hz by a strain gauge measurement

system (StrainBook/616, Measurement Computing, Norton, MA, USA). This equipment allows

simultaneous measurements of eight channels. The measurement system was connected to a laptop

Sensors 2015, 15 2012

computer equipped with data acquisition software (Waveview 7.15, Measurement Computing) that could

save the strain values of each measurement channel in a different data file.

Table 2. Properties of the soils corresponding to the trial plots.

Field Humidity (%) Soil Type Texture

1 9.3 clayey-silty-loam 16.1% sand; 49.3% loam; 35.6% clay 2 8.1 clayey-silty-sandy 45.5% sand; 23.3% loam; 31.2% clay

2.3. Statistical Analysis

The micro-strains obtained by the strain gauges were corroborated in their normality by the

Kolmogorov-Smirnov test (p < 0.001) and their homoscedasticity with respect to the parameters

forward speed and application depth by the Levene test (p < 0.001). Therefore, non-parametric

methods were required for the analysis [28].

To carry out the study, the strain values obtained were treated as absolute values. A positive or

negative value indicates that the gauge is being subjected to tension or compression, respectively.

The reliability of the strains obtained in the measurement channels was evaluated by a t-test.

To ensure independence of observations, a bootstrap of 1000 samples without stratification was

conducted [29].

Differences between the micro-strains obtained by the strain gauges depending on the field texture

were statistically analysed by the Mann-Whitney U-test. The corresponding differences depending on the

forward speed or application depth were analysed by the Kruskal-Wallis test. In the latter case,

post-hoc analyses of differences between levels of each parameter were performed by the

Mann-Whitney U-test.

3. Results and Discussion

3.1. Considerations of the FEM Design

The results of the experimental tests allowed to analyse the five initial hypotheses of load cases

applied to the numerical analysis developed by the FEM. Table 3 shows the comparison between the

numerical and experimental results obtained by gauges 1–4, corresponding to an application depth of

0.17 m considering the entire range of forward speeds and soil types. Data were acquired by using 8

measurement channels. In this sense, Channels 1–3 corresponded to the rosette (gauge 1). Channels 4, 6,

and 7 corresponded to the three linear strain gauges (gauges 2–4, respectively). Channel 5 corresponded

to a linear strain gauge, which was installed to correct the effects of noise and temperature recorded by

the strain gauges.

The experimental tests allowed validation of the prototype design. The correlation between

numerical and experimental results showed that the range of load hypotheses considered (445 to 5000 N)

correctly represents the actual behaviour of the implement, considering that the experimental data

corresponding to the application depth of 0.17 m were those at the worst working condition and the

effect of velocity was insubstantial as shown below. Considering an application depth of 0.17 m

(Table 3), the stresses and strains recorded in the field were similar to those simulated by numerical

Sensors 2015, 15 2013

analysis at a load case of 5000 N which was the largest load case applied to the numerical model. This

suggests the use of high load conditions in the design phase.

Table 3. Stresses and strains registered by the gauges for numerical and experimental

results corresponding to an application depth of 0.17 m, considering the entire range of

forward speeds and soil types.

Gauge Load Cases Considered in the Numerical Analysis (FEM) Experimental

Results 445 N 800 N 2610 N 4500 N 5000 N

1 (rosette) 2.14 MPa 2.98 MPa 9.49 MPa 16.98 MPa 17.81 MPa 17.61 MPa 2 (linear) 3.87 μξ 6.77 μξ 16.25 μξ 32.66 μξ 36.01 μξ 40.23 μξ 3 (linear) −17.28 μξ −22.25 μξ −39.69 μξ −79.88 μξ −85.13 μξ −88.76 μξ 4 (linear) 60.09 μξ 92.81 μξ 261.02 μξ 481.00 μξ 541.10 μξ 549.40 μξ

Data recorded by the measurement gauges showed that the prototype structure behaved similarly in

the two fields tested, with higher strain values for the loam texture (field 1). The strains recorded by

Channel 7 were the highest among all channels in both fields. Channel 6 corresponded to the linear

strain gauge placed in the main bar of the fixed chassis (gauge 4). These strains are caused by bending

due to the force applied at the furrow opener. The highest strains were recorded in field 1. The strains

recorded in this field, at a forward speed of 7 km/h and an application depth of 0.17 m, are shown in

Figure 5. Of all possible configurations, this configuration yielded the maximum strains in all gauges.

The Von Mises stresses calculated from the data registered by the strain gauges for this configuration

are shown in Table 4. The minimum safety coefficient of all components was 1.9. These results, in

addition to the numerical analysis developed, show that the prototype design is valid.

Figure 5. Strains (με) recorded in the experimental test in the field with loam texture

(field 1), at a forward speed of 7 km/h and an application depth of 0.17 m.

The results obtained in the experimental tests validated the design of the prototype which was able

of creating narrow tunnels with the furrow opener of 2 cm width at different forward speeds and

application depths. The methodology of simulating the performance of the implement by introducing

static loads on the furrow opener with a FEM model was appropriate because the numerical results

were well correlated to those obtained in the experimental tests.

Sensors 2015, 15 2014

Table 4. The von Mises stresses and safety coefficients obtained from measurements

registered by the strain gauges in the field with loam texture (field 1), at a forward speed of

7 km/h and an application depth of 0.17 m.

Strain Gauge Stress (MPa) Yield Strength (MPa) Safety Coefficient

1 45.81 360.00 7.86 2 0.68 360.00 529.10 3 33.48 360.00 10.75 4 187.27 360.00 1.92

3.2. Effect of Forward Speed and Depth

The effects of forward speed and application depth on the mechanical performance of the

implement chassis were analysed by considering the information obtained from the strain gauges. As

an example, Figure 6 shows the micro-strains recorded by the strain gauges for a pathway of 400 m in

field 2 (sandy) at a forward speed of 4.5 km/h and an application depth of 0.15 m.

Figure 6. Strains (με) recorded in the experimental test in field 2 (sandy) at a forward

speed of 4.5 km/h and an application depth of 0.15 m. Rosette: Channels 1–3; 3 Linear

strain gauges: Channels 4, 6, and 7; Reference strain gauge: Channel 5.

The micro-strains measured by the reference gauge were not significantly different from zero

(0.0109 ± 0.00607; Bias bootstrap = −0.33 × 10−4, t = 1.673, p = 0.075). Therefore the measurements

obtained in the other gauges were considered as valid.

Table 5 shows the means and standard deviations of the micro-strains recorded by the seven

measurement channels in the two fields tested. The table shows that the strains obtained from the field

with loam texture are significantly higher than the results recorded in the field with sandy texture. In

addition, the strains obtained by the seven gauges vary widely. This variation is expected because the

gauges are placed in different components of the chassis, which operate differently. The 95%

confidence intervals of the micro-strains of each gauge, standardised according to the soil type, are

shown in Figure 7.

Sensors 2015, 15 2015

Table 5. Means and standard deviations of micro-strains (με) measured by gauges

depending on the soil tested. Mean differences tested with the Mann-Whitney U-test.

SS: Standardised Statistic.

Measurement Channel

Soil Probability

1: Loam (n = 25,148) 2: Sandy (n = 12,322) SS p 1 13.937 ± 5.373 11.477 ± 3.628 −41.382 <0.001 2 67.595 ± 15.465 54.131 ± 18.140 −63.186 <0.001 3 41.054 ± 22.446 13.053 ± 10.258 −119.220 <0.001 4 31.757 ± 17.167 21.043 ± 11.806 −60.822 <0.001 5 1.758 ± 0.955 1.126 ± 0.895 −63.235 <0.001 6 72.241 ± 36.945 26.839 ± 20.938 −111.349 <0.001 7 479.399 ± 156.796 260.570 ± 102.492 −118.589 <0.001

Figure 7. 95% confidence intervals of all micro-strains standardised according to soil type.

Tables 6 and 7 show the average micro-strains measured by the gauges as a function of the forward

speed and application depth, respectively. The analysis results show that micro-strains recorded at

different forward speeds were significantly different in all gauges. Maximum values were registered at

low velocities for Channels 1–5 and at the maximum velocity for Channels 6 and 7. However,

although the differences were significant, the micro-strains did not show great variation depending on

the forward speed from the viewpoint of designing the structure of the machine.

Micro-strains obtained at different working depths were significantly different for all strain gauges.

In addition, the differences increased as the application depth increased. In this case, the micro-strains

showed a great variation depending on the application depth from the design perspective. Most gauges

showed an increment in the recorded values bigger than 50% when the application depth changed from

0.12 to 0.17 m. The 95% confidence intervals of the micro-strains of each gauge standardised

according the soil texture at different forward speeds and the application depths are shown in

Figures 8 and 9, respectively.

Sensors 2015, 15 2016

Table 6. Average micro-strains (με) measured by gauges at different forward speeds.

One-way ANOVA: forward speed (km/h). Mean differences tested with the Kruskal-Wallis

test. Different letters indicate significant differences (p < 0.05) obtained through the

Mann-Whitney U-test for a specific measurement channel considering different forward speeds.

Measurement

Channel

Forward Speed (km/h) Probability

4.5 (n = 15,055) 5.5 (n = 12,482) 7.0 (n = 9,933) Chi-Square p 1 13.200 ± 4.342b 13.373 ± 5.888c 12.711 ± 4.699a 53.771 <0.001

2 65.039 ± 15.040b 62.391 ± 22.796b 61.305 ± 12.622a 472.309 <0.001

3 31.042 ± 23.714a 33.403 ± 24.290c 31.107 ± 21.463b 78.746 <0.001

4 29.346 ± 19.420b 27.802 ± 15.635ab 27.089 ± 11.507a 14.539 0.001

5 1.803 ± 1.153c 1.484 ± 0.844b 1.249 ± 0.729a 1,489.202 <0.001

6 55.857 ± 38.568a 59.155 ± 40.071c 57.195 ± 37.898b 40.770 <0.001

7 394.909 ± 170.765a 417.428 ± 180.190b 413.871 ± 172.470b 143.294 <0.001

Table 7. Means and standard deviations of micro-strains (με) measured by gauges at

different application depths. Mean differences tested with the Kruskal-Wallis test.

Different letters indicate significant differences (p < 0.05) obtained through the

Mann-Whitney U-test for a specific measurement channel considering different depths.

Measurement

Channel

Depth (cm) Probability

12 (n = 12,468) 15 (n = 12,250) 17 (n = 12,482) Chi-Square p

1 11.068 ± 3.723a 11.917 ± 4.265b 16.401 ± 5.163c 7,374.958 <0.001

2 58.751 ± 11.747a 58.932 ± 21.119b 71.826 ± 15.139c 5,013.109 <0.001

3 13.624 ± 8.225a 29.596 ± 15.610b 52.303 ± 23.900c 16,229.685 <0.001

4 19.501 ± 9.333a 24.967 ± 13.301b 40.234 ± 17.666c 10,368.368 <0.001

5 1.092 ± 0.684a 1.664 ± 1.055b 1.893 ± 0.985c 4,382.641 <0.001

6 26.852 ± 18.524a 56.291 ± 30.119b 88.756 ± 37.141c 15,540.010 <0.001

7 269.405 ± 94.144a 403.358 ± 133.349b 549.405 ± 160.432c 15,625.539 <0.001

Figure 8. 95% confidence intervals of all micro-strains standardised according to soil

texture at different forward speeds.

Sensors 2015, 15 2017

Figure 9. 95% confidence intervals of all micro-strains standardised according to soil

texture at different application depths.

The results showed that the application depth had a greater effect on the behaviour of the chassis

than did the forward speed. In addition, the effects of the application depth were linear: as the

application depth increased, the strains in the chassis also increased. In contrast, as the forward speed

increased, the strains on the chassis remained roughly constant.

These findings are concordant with those found in other studies. Draught forces increase

substantially for a tine with increased depth, both on open soil [30] and in grassland [31,32]. The draught

force for rigid tines reportedly increases linearly with speed for sandy clay loam and is linear with a

discontinuity for clay [33]. Others studies have not found an increase in forces for injector tines with

increased speed [34].

4. Conclusions

A prototype device for underground application of rodenticide bait to control the Mediterranean

pocket gopher in fruit orchards was designed and tested by using the FEM. Strain gauges were used in

the field to validate the design phase and yield information on the structural performance of the

implement at different speeds and application depths. Both forward speed and depth had a significant

effect on the mechanical behaviour of the chassis. In particular, the application depth was the critical

parameter that affected the strains on the structure of the implement. The effects of the application

depth on the strains were linear such that strains increased with depth. In contrast, strains remained

roughly constant regardless of the forward speed.

Acknowledgments

This project could not have been possible without the contribution of the Plant Protection Centre of

the Agriculture and Food Department of the Aragon Government with its financial support and

technical staff and the company AGROPAL.

Sensors 2015, 15 2018

Author Contributions

Authors contributed equally to this work. H. Malón contributed to all phases of the work (design,

testing, data analysis and writing). A. Boné and M. Vidal contributed to design, and testing phases.

J. Aguirre contributed to the testing, data analysis, and writing phases, and F.J. García-Ramos

contributed to the coordination of the work as well as the design, testing, and writing phases.

Conflicts of Interest

The authors declare no conflict of interest.

References

1. Baldwin, R.A.; Marcum, D.B.; Orloff, S.B.; Vasquez, S.J.; Wilen C.A.; Engeman, R.M. The

influence of trap type and cover status on capture rates of pocket gophers in California. Crop. Prot.

2013, 46, 7–12.

2. Sullivan, T.P.; Sullivan, D.S.; Hogue, E.J. Demography of montane voles in old field and orchard

habitats in southern British Columbia. Northwest Sci. 2003, 77, 228–236.

3. O’Brien, J.M. B-177: Voles. In Prevention and Control of Wildlife Damage; Hygnstrom, S.E.,

Timm, R.M., Larson, G.E., Eds.; University of Nebraska-Lincoln: Lincoln, NE, USA, 1994.

4. Jacob, J.; Tkadlec, E. Rodent outbreaks in Europe: Dynamics and damage. In Rodent Outbreaks:

Ecology and Impacts; Singleton, G., Belmain, S., Brown, P.R., Hardy, B., Eds.; International Rice

Research Institute (IRRI): Los Baños, Philippines, 2010; pp. 207–224.

5. Walther, B.; Fülling, O.; Malevez, J.; Pelz, H.J. How expensive is vole damage? In Proceedings

to the Conference; Boos, M., Ed.; Fördergemeinschaft Ökologischer Obstbau.e.V.: D-Weinsberg,

Germany, 2008; pp. 330–334.

6. Virchow, D.R.; Hygnstrom, S.E.; Anderson, B.E. Using Burrow Builders for Pocket Gopher Control;

NebGuide 1510; University of Nebraska-Lincoln Extension: Lincoln, NE, USA, 2003.

7. Jokic, G.; Vuks, P.; Vuks, M. Comparative efficacy of conventional and new rodenticides against

Microtus arvalis (Pallas, 1778) in wheat and alfalfa crops. Crop. Prot. 2009, 29, 487–491.

8. Chen, J.N.; Coquille, J.C.; Douzals, J.P.; Sabre, R; Andreux, F. Frequency composition of traction

and tillage forces on a mole plough. Soil Tillage Res. 1997, 44, 67–79.

9. Werner, S.J.; Nolte, D.L.; Provenza, F.D. Proximal cues of pocket gopher burrow plugging

behavior: Influence of light, burrow openings, and temperature. Physiol. Behav. 2005, 85, 340–345.

10. Giraudoux, P.; Tremollières, C.; Barbier, B.; Defaut, R.; Rieffel, D.; Bernard, N.; Lucot, E.;

Berny, P. Persistence of bromadiolone anticoagulant rodenticide in Arvicola terrestris populations

after field control. Environ. Res. 2006, 102, 291–298.

11. Stafford, J.V. The performance of a rigid tine in relation to soil properties and speed. J. Agric.

Eng. Res. 1979, 24, 41–56.

12. Gebresenbet, G.; Jönsson, H. Performance of seed drill coulters in relation to speed, depth and

rake angles. J. Agric. Eng. Res. 1992, 52, 121–145.

13. Owende, P.M.O.; Ward S.M. Characteristic loading of light mouldboard ploughs at slow speeds.

J. Terramech. 1996, 33, 29–53.

Sensors 2015, 15 2019

14. Rodhe, L.; Rydberg, T.; Gebresenbet, G. The influence of shallow injector design on ammonia

emissions and draught requirement under different soil conditions. Biosyst. Eng. 2004, 89, 237–251.

15. Shoji, K. Forces on a model spot plough. Biosyst. Eng. 2004, 87, 39–45.

16. Mouazen, A.M.; Duerinckx, K.; Ramon, H.; Anthonis, J. Soil influences on the mechanical

actions of a flexible spring tine during selective weed harrowing. Biosyst. Eng. 2007, 96, 7–18.

17. Chaudhuri, D. Performance evaluation of various types of furrow openers on seed drills. A

Revision. J. Agric. Eng. Res. 2001, 79, 125–137.

18. Miralbes, R.; Castejon, L. Fatigue design of tanker semi-trailers. DYNA 2010, 85, 480–448.

19. Carrera, M.; Castejon, L.; Miralbes, R.; Valladares, D. Behaviour IA rear underrun protection

system on car-to-tank vehicle impact used for fuel transportation. Int. J. Heavy Veh. Syst. 2010, 17,

199–215.

20. Gebregziabher, S.; Mouazen, A.M.; van Brussel, H.; Ramon, H.; Meresa, F.; Verplanckee, H.;

Nyssen, J.; Behailu, M.; Deckers, J.; de Baerdemaeker, J. Design of the Ethiopian ard plough

using structural analysis validated with finite element analysis. Biosyst. Eng. 2007, 97, 27–39.

21. Formato, A.; Faugno, S.; Paolillo, G. Numerical simulation of soil-plough mouldboard

interaction. Biosyst. Eng. 2005, 92, 309–316.

22. Duerinckx, K.; Mouazen, A.M.; Anthonis, J.; Ramon, H. Effects of spring-tine settings and

operational conditions on the mechanical performance of a weed harrow tine. Biosyst. Eng. 2005,

91, 21–34.

23. Bogrekci, I.; Godwin, R.J. Development of a mechanical transducer for real-time soil tilth

sensing. Biosyst. Eng. 2007, 98, 127–137.

24. Collins, B.A.; Fowler, D.B. Effect of soil characteristics, seeding depth, operating speed, and

opener design on draft force during direct seeding. Soil Tillage Res. 1996, 39, 199–211.

25. Darmora, D.P.; Pandeyb, K.P. Evaluation of performance of furrow openers of combined seed and

fertiliser drills. Soil Tillage Res. 1995, 34, 127–139.

26. Sánchez-Girón, V.; Ramírez, J.J.; Litago, J.J.; Hernanz, J.L. Effect of soil compaction and water

content on the resulting forces acting on three seed drill furrow openers. Soil Tillage Res. 2005,

81, 25–37.

27. Onwualu, A.P.; Watts, K.C. Draught and vertical forces obtained from dynamic soil cutting by

plane tillage tools. Soil Tillage Res. 1998, 48, 239–253.

28. Montgomery, D.C.; Runger, G.C. Applied Statistics and Probability for Engineers, 3rd ed.;

John Wiley & Sons, Inc.: New York, NY, USA, 2003.

29. Efron, B.; Tibshirani, R.J. An Introduction to the Bootstrap; Chapman & Hall/CRC Press:

New York, NY, USA, 1994.

30. Schaaf, D.E.; Hann, S.A.; Lindwall, C.W. Performance evaluation on furrow openers cutting

coulters and press wheels for seed drills. In Crop Production with Conservation 80s; ASAE

Publication: St Joseph, MI, USA, 1981; Volume 7, pp. 76–84.

31. Huijsmans, J.F.; Hol, J.M.G.; Hendriks, M.M. Effect of application technique, manure

characteristics, weather and field conditions on ammonia volatilization from manure applied to

grassland. Neth. J. Agric. Sci. 2001, 49, 323–342.

32. Chen, Y. A liquid manure injection tool adapted to different soil conditions. Trans. ASAE 2002,

45, 1729–1736.

Sensors 2015, 15 2020

33. Stafford, J.V. An application of critical state soil mechanics: The performance of rigid tines.

J. Agric. Eng. Res. 1981, 26, 387–401.

34. Rahman, S.; Chen, Y. Laboratory investigation of cutting forces and soil disturbance resulting

from different manure incorporation tools in a loamy sand soil. Soil Till. Res. 2001, 58, 19–29.

© 2015 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article

distributed under the terms and conditions of the Creative Commons Attribution license

(http://creativecommons.org/licenses/by/4.0/).